L0 Regularization of Field-Aware Factorization Machine through Ising Model

arXiv:2403.01718v1 Announce Type: new
Abstract: We examined the use of the Ising model as an L0 regularization method for field-aware factorization machines (FFM). This approach improves generalization performance and has the advantage of simultaneously determining the best feature combinations for each of several groups. We can deepen the interpretation and understanding of the model from the similarities and differences in the features selected in each group.

abstract arxiv cond-mat.mtrl-sci cs.lg factorization feature interpretation machine machines performance regularization through type understanding